This paper proposed the use of vision based Fuzzy control approaches for autonomous navigation tasks with Unmanned Aerial Vehicles (UAVs). It is shown the advantages of using RGB cameras as the sensor onboard UAVs and the advantages of using Fuzzy logic controllers. It is explained how to set a vision...

Z. Taká c in [16] introduced the aggregation operators on any subalgebra of M (set of all fuzzy membership degrees of the type-2 fuzzy sets, that is, the functions from [0,1] to [0,1]). Furthermore, he applied the Zadeh’s extension principle (see [24]) to obtain in [16, 17] a set of aggregation operators...

The reliability of the fuzzy scale for assessing the responses of a person in an opinion questionnaire (which is usually treated as a Likert-type questionnaire) is analyzed. Thus, a comparison between a classical Likert scale-based questionnaire and its fuzzy rating scale-based version in terms of their...

Welfare and close related issues, like poverty and ine-quality, are multidimensional as they involve not only income, but also education, health or labour. This paper aims to measure the dependence among dimensions us-ing copula-based coefficients. This approach focuses on the positions of the individuals...

This work presents a novel Genetic Fuzzy System (GFS), called Genetic Programming Fuzzy Inference System for Regression problems (GPFISRegress). It makes use of Multi-Gene Genetic Programming to build the premises of fuzzy rules, including t-norms, negation and linguistic hedge operators. GPFIS-Regress...

In geophysics, signals come with noise. It is desirable to minimize the effect of this noise. If we knew the probabilities of different values of signal and noise, we could use statistical filtering techniques. In geophysics, however, we rarely know the exact values of these probabilities; instead, we...

In this paper, the theoretical foundations of generalised fuzzy Bayesian Network based on Vectorial Centroid defuzzification is introduced. The extension of Bayesi-an Network takes a broad view by examples labelled by a fuzzy set of attributes, instead of a classical set. Com-bining fuzzy set theory...

Fuzzy logic has been a useful tool for modeling complex problems, with the use of fuzzy variables and fuzzy rules, and in this paper we use a fuzzy system for parameter adaptation in the Ant Colony Optimization (ACO meta-heuristic). In this case we perform the dynamic adaptation of Alpha and Rho parameters;...

Inverse reinforcement learning is tried to search a reward function based on Markov Decision Process. In the IRL topics, experts produce some good traces to make agents learn and adjust the reward function. But the function is difficult to set in some complicate problems. In this paper, Inverse Reinforcement...

A statistical analysis of Type-1 and Interval Type-2 Fuzzy Logic in dynamic parameter adaptation in the Bee Colony Optimization algorithm (BCO) is presented in this paper. The Bee Colony Optimization meta-heuristic belongs to the class of Nature-Inspired Algorithms. The objective of the work is based...

The emergence of more powerful computational techniques has stimulated the development and study of more sophisticated models for portfolio selection problem including further constraints and further financial and non-financial decision criteria. In this paper, we propose a hybrid approach composed of...

Recently, two new families of fuzzy implication functions called probabilistic implications and probabilistic S-implications were introduced by Grzegorzewski [6, 7, 9]. They are based on conditional copulas and make a bridge between probability theory and fuzzy logic. In this paper we generalize these...

Many real-world decision making problems require multiple criteria which can be from different nature. This implies to define a heterogeneous context with different types of information that experts will use to provide their assessments. But sometimes, experts do not have enough knowledge or information...

Recently, Grzegorzewski [9] introduced two new families of fuzzy implication functions called survival implications and survival S-implications. These two classes of multivalued implications are based on conditional copulas. In the same article the author gave a motivation to his ideas and he analyzed...

We present DC* (Double Clustering with A*) as an information granulation method specifically suited for deriving interpretable knowledge from data. DC* is based on two main clustering stages: the first is devoted to compressing multi-dimensional data into few prototypes that grab the main relationships...

A fuzzy set can be seen as a measure of the meaning of a predicate in a given universe. Generally, a predicate covers some elements of the universe and not others. In this paper the problem of determining the properties a fuzzy set should check to cover elements not covered by a predicate represented...

Finding strongly standard complete axiomatizations for t-norm based fuzzy logics (i.e. complete for deductions with infinite sets of premises w.r.t. semantics on the real unit interval [0, 1]) is still an open problem in general, even though results are already available for some particular cases like...

Digital images are generally created as discrete measurements of light, as performed by dedicated sensors. Consequently, each pixel contains a discrete approximation of the light inciding in a sensor element. The nature of this measurement implies certain uncertainty due to discretization matters. In...

The paper shows how a specific notion of consistency based on a definition of interactions of decision goals is linked with the notion of separability. Subsets of deci-sion alternatives for which additive aggregation as deci-sion making concept is allowed are systematically iden-tified. These subsets...

In multi-criteria decision problems the relative importance of alternatives is computed from preference matrices, which come from experience and can possibly be inconsistent. Two consistency types of preferences are studied in the paper. The ordinal consistency preserves the order in which the alternatives...

In this paper we propose a general procedure to represent a fuzzy set that may be non-normal and/or non-convex. This representation will be offered by an interval and a crisp value. This idea is useful either in optimization and decision making problems or in defuzzification step of a fuzzy inference...

Sugeno integral is one of the basic aggregation operations on a qualitative scale where only minimum and maximum, as well as order-reversing maps are allowed. Recently some variants of this aggregation operation, named soft and drastic integrals, have been introduced in a previous work by three of the...

In this paper, we propose the use of energy load profiles to learn human activities. An energy load profile determines the energy consumption of an appliance during a specific interval of time. We propose the use of clustering techniques to group the different profiles according to their temporal consumption....

The study of energy efficiency in buildings is an active field of research. Modelling and predicting energy related magnitudes leads to analyse electric power consumption and can achieve economical benefits. In this study, machine learning techniques are applied to predict active power in buildings....

The median of a fuzzy random variable has been extended either by applying Zadeh’s extension principle or by minimizing its mean distance w.r.t. a fuzzy number when a certain L1 metric is considered. This paper aims to analyze connections between both approaches along with some properties of the first...

Since its launch in December 2013, the Gaia space mission has collected and continues to collect tremendous amounts of information concerning the objects that populate our Galaxy and beyond. The international Gaia Data and Analysis Consortium (DPAC) is in charge of developing computer algorithms that...

The way human beings communicate is contextdependent and it is not easily reproduced on traditional computer systems. We propose combined advances in Context-aware Computing and Fuzzy Databases with the aim of producing more intelligent, flexible and personalized systems. We focus on the interaction...

This paper presents an automatic method to design interval type-2 fuzzy systems for load forecasting applications using a memetic algorithm. This hybridisation of a variable-length genetic algorithm and a gradient descent method allows for concurrent learning of the system’s parameters and structure...

The aim of the 2015 IFSA-EUSFLAT International Time Series Competition, Computational Intelligence in Forecasting (CIF), is to evaluate the performance of computational intelligence-based approaches to forecast time series of different nature. The participants must propose a unique consistent methodology...

Currently there are not many data mining method available to solve the classification task in datasets with low quality values. In this paper we propose a method of imputation/classification based on neighborhood that can work with nominal and numerical attributes which can contain low quality values....

The purpose of these notes is to introduce the concept of a many-valued relation and to study two, in a certain sense dual, categories of such relations. Besides, we apply the concept of a manyvalued relation to the description of different approaches, both fixed-based and variable-based, to Fuzzy Topology...

Global real estate investments have been one of the popular investment areas since developments in trans-portation vehicles among countries, significant reduc-tion in travelling costs, and suitable legal arrangements for purchasing real estates in a foreign country have made it attractive. This investment...

The suggested approach, FMAA (Fuzzy Multicriteria Acceptability Analysis), assimilates uncertainties/ imprecisions of objective values and subjective judgments within the discrete Multi-Criteria Decision Analysis (MCDA). The presented algorithm for FMAA implementation utilizes fuzzy criterion values...

Fuzzy Sets theory has been applied in many fields to handle uncertainty, which can be reflected on the membership degree of the objects belonging to a set. Moreover, Hesitant Fuzzy Sets are useful whenever there is indecision among several possible values for the preferences over objects in the process...

A novel way for addressing one-sided hypothesis tests for the mean of unable to observe real random variables from which we have information provided in terms of interval data is proposed. For this purpose, a measure of similarity between intervals is considered and the classical one-sided hypothesis...

Liking allows users of Social Networks, blogs and online magazines to express their support of posts and artifacts by a simple click. Such function is very popular but lacks semantic power, and some platforms have augmented it by allowing to choose a pictographic depiction corresponding to a feeling....

A multi-criteria decision making (MCDM) method, as its own name suggests, is for use in situations when more than one criterion must be considered. In this work, we will focus on the Analytic Hierarchy Process (AHP), one of the well-known and most widely used MCDM approaches. Despite the extensive application...

We propose linguistic associations mining as a technique to create the models of the multivariate time series. We define various linguistic evaluative expressions on the range of the values of the time series and variables derived from them. We mine linguistic associations then and interpret them as...

Urban growth and the development of urban plans make cities grow and substantially alter, in relatively short time periods, their land covers and land uses (LULC). To take control of this urban growth, it is im-portant to create and update the LULC database. In this work, a method to automatically extract...

This paper describes the optimization of the fuzzy inte-grators in Ensembles of ANFIS models for time series prediction, this with emphasis on its application to the prediction of Mackey-Glass time series, so this bench-mark time series is used to the test of performance of the proposed ensemble architecture....

Transfer learning provides an approach to solve target tasks more quickly and effectively by using previously-acquired knowledge learned from source tasks. Most of transfer learning approaches extract knowledge of source domain in the given feature space. The issue is that single perspective can t mine...

Fuzzy graph, fuzzy directed way, accessible degree, fuzzy transitive closure, reachability degree, strong connection degree, vitality degree, fuzzy set of vitality.

Global and balanced performance measurement in Qual-ity Policy Deployment is a key element of quality man-agement in public Higher Education Institutions (HEI´s). This paper describes the design of a fuzzy linguistic model for measuring Quality Policy Deployment in a Colombian public HEI. The proposed...

classification based on the One-vs-One decomposition strategy has shown a high quality for addressing those problems with multiple classes, even if the learning model enables the discrimination among several concepts. The main phase of the pairwiselearning is the decision process, where the outputs of...

Rational Pavelka Logic does not admit infinitesimals. We argue that infinitesimals are important in logic and we present an alternative approach which admits them. It is built up in a similar style, but based on the Chang’s perfect MV-algebra. We prove a partial result towards the completeness of this...

Recent developments in computing and hardware manufacturing are allowing many pieces of software to be embedded in general-purpose, low-cost devices. This work presents and tests the feasibility and performance of implementing, in such a device, a previously developed unified fuzzy controller for managing...

The electricity market has been significantly changing in the last decade. The deployment of smart meters is enabling the logging of huge amounts of data relating to the operations of utilities with the potential of being translated into valuable knowledge on the behaviour of consumers. This work proposes...

We study classroom discussions to obtain a fuzzy summary of the quality of teaching and opportunities to learn mathematics created in whole-class settings. We consider the ten rubrics of the Instructional Quality Assessment and make a fuzzy interpretation of this tool. We selected two problems of proportionality...

Discrete convolution is commonly used operation in the image processing field. The technique modifies an input image in various ways by scalable and easy computation. We are able to achieve many applications such as edge detection, noise reduction or artistic filtering, by selection of the proper kernel....

Advances in distributed networking have resulted in an explosion in size of modern datasets while storage and processing power continue to lag behind. This requires the need for algorithms that are efficient in terms of number of measurements and running time. To combat challenges associated with large...

The aim of this contribution is to show the opportunities of applying of fuzzy time series models to predict multiple heterogeneous time series, given at International Time Series Forecasting Competition [http://irafm.osu.cz/cif/main.php]. The dataset of this competition includes 91 time series of different...

Conditioning for (non-additive) uncertainty measures is still an open problem. These measures can arise through probabilistic inference procedures, as in the case of possibility measures, that can be seen as the upper envelope of the extensions of a probability when the corresponding algebras are weakly...

The morphological gradient is a widely used edge detector for grey-level images in many applications. In this paper, we generalize the definition of the morphological gradient of the fuzzy mathematical morphology based on t-norms. Concretely, instead of defining the morphological gradient from the usual...

Consensus reaching processes play a key role in the resolution of many group decision making problems, in which it is desirable to obtain a highly acceptable solution to all individuals involved in the problem. However, not much interest has been put on defining appropriate metrics to evaluate in further...

Redundancy is a handicap in association rules. It becomes a limitation to use rules models in order to support the decision-making process. A technique based on user knowledge has been proposed recently, which aims at eliminating redundancy. However, it ignores the imprecise nature of knowledge. In this...

In this paper we present a procedure to obtaining the solution of a fuzzy differential equation via differential inclusions. This procedure is an alternative approach, based on optimal control tools, to obtaining a description exact of a fuzzy solution for a large class of nonlinear fuzzy differential...

Evolving classification models are designed to solve online tasks with demands restricting computational power and memory. The present paper proposes an evolving version of an established fuzzy classification approach based on fuzzy pattern classes. The approach incorporates a novel type of virtual sample...

In this paper, we discuss three tasks of mining information from time series, namely finding intervals with monotonous trend, evaluation of it in sentences of natural language, and summarizing information using intermediate quantifiers. The mined information is presented in simple sentences of natural...

Based on previous investigations, we have proposed two different methods to extend lattice-valued fuzzy connectives (t-norms, t-conorms, negations and implications) and other related operators, considering a generalized notion of sublattices. Taking into account the obtained results that we have obtained...

While online product reviews are valuable sources of information to facilitate consumers’ purchase decisions, it is deemed meaningful and important to distinguish helpful reviews from unhelpful ones for consumers fac-ing huge amounts of reviews nowadays. Thus, in light of review classification, this...

In this paper, we introduce and analyze a class of fuzzy poverty measures based on exponential means. Since poverty is a vague notion, individuals should not be classified in poor or non-poor. In our proposal, we have associated a degree of poverty to each income through a fuzzy membership function....

In the previous papers, we introduced a general principle for an introduction of new intermediate quantifiers and proved that generalized square of opposition works with them accordingly. This paper is devoted to interpretation of an intermediate quantifier “Many” and to analysis of generalized 5-square...

Attribute reduction is an important step in order to decrease the computational complexity to derive information from databases. In this paper, we extend the notions of reducts and bireducts introduced in rough set theory for attribute reduction purposes and let them work with similarity relations defined...

In this work we construct linear orders between pairs of intervals by using aggregation functions. We apply these orders in a decision-making problem where the experts provide their opinions by means of interval-valued fuzzy sets.

Short-term stream flow forecasts are required for simulation, optimization, and decision-making purposes in applications ranging from hydropower planning to flood prevention. The particular case of one-day ahead stream flow forecasting is an important but difficult problem that has been increasingly...

This paper examines the problem of recognition of col-ored objects for the NAO humanoid robot using camer-as. Based on the ability of fuzzy systems to approxi-mate any mapping, the input-output behavior between the triplet {H, S, V} and the linguistic output colors is represented by a Sugeno fuzzy system....

In the paper we solve the problem of recognizing the roadbed using information about its possible typical designs. As shown on the paper typical designs can be adequately described by the set of fuzzy features, derived from the polygonal representation of the roadbed cross profile. The recognition is...

The Truck and Trailer Routing Problem, TTRP, is an extension of the well-known Vehicle Routing Problem. This problem consist of a heterogeneous fleet composed of trucks and trailers to serve a set of customers. Most of models used in the literature assume that the data available are accurate, but in...

Despite convex mathematical optimization methods be applied to general linear optimization problems it can also be applied in a special class of nonlinear optimization. As ambiguity and vagueness are natural and ever-present in real-life situations requiring solutions, it makes perfect sense to attempt...

Paving is a method for constructing new operations from a given one. We will show that this method can be used to construct associative, commutative and monotone operations from particular given operations (from basic ‘paving stones’). We will discuss properties of the resulting operations by considering...

The disposal of many families of fuzzy implications is crucial to handle the great number of applications these operators have. In this work, the class of fuzzy (OP)-polynomial implications is introduced as those fuzzy implications satisfying the ordering property (OP) whose expression in the region...

In this paper, we present a way to define the concept of fuzzy image segmentation, which has not been clearly defined in the literature. In this work the term Fuzzy image segmentation is characterized by means of a fuzzy set over the set of edges, which can be understood as the fuzzy boundary of the...

This paper presents a comparative analysis of the performance of fuzzy approaches on the task of predicting customer review ratings using a computational intelligence framework based on a genetic algorithm for data dimensionality reduction. The performance of the Fuzzy C-Means (FCM), a neurofuzzy approach...

Synchrony among neuronal impulses (or spikes) plays, according to some of the most prominent neural coding hypotheses, a central role in information processing in biological neural networks. When dealing with multiple electrode recordings (i.e., spike trains) modelers generally characterize synchrony...

Recently, some extensions of the classical fuzzy sets are studied in depth due to the good properties that they present. Among them, in this paper finite interval-valued hesitant fuzzy sets are the central piece of the study, as they are a generalization of more usual sets, so the results obtained can...

The evaluation of the health status of a population is a key question in Health Policy. The measurement of the health status is a relevant process to keep and improve the countries’ level of economic development. In spite of this relevance, the current evaluation methodologies are not sufficiently well-defined...

An approach to construct a new classifier called an intuitionistic fuzzy decision tree is presented. Well known benchmark data is used to analyze the performance of the classifier. The results are compared to some other popular classification algorithms. Finally, the classifier behavior is verified while...

In this work we deal with the problem of using OWA operators in color image reduction algorithms. For this reason, we study OWA operators defined on an arbitrary finite lattice endowed with a t-norm and a t-conorm. In the case of RGB color images, we apply OWA operators defined on a finite product lattice....

Bipolar queries consist of negative and positive conditions specifying the features that are making data sought, respectively, rejected and accepted. A possible strategy to evaluate such bipolar queries is to combine matching degrees of both conditions using the and possibly operator. We studied this...

The inherent interpretability properties of fuzzy rule-based classification systems (FRBCSs) are undoubtedly one of their major advantages when compared to conventional black-box classifiers. In this paper we present a preliminary study of how the socalled technique of feature construction can prove...

The paper defines and studies ukasiewicz-like triangular subnorms, i.e., triangular subnorms such that their level sets are obtained as unions of the level sets of the ukasiewicz triangular norm. As a result, the paper gives a characterization of these operations.

In this work we propose an objective function to obtain an interval-valued fuzzy clustering. After the process of optimization we obtain an interval-valued fuzzy partition in which the length of the intervals depends on the position of the points with respect of the clusters.

This paper uses a methodology based in fuzzy sets theory in order to describe the interaction between the prey, Aphis glycines (Hemiptera: Aphididae) - the soybean aphid, and its predator, Orius insidiosus (Hemiptera: Anthocoridae) and to propose a chemical control for soybean aphid. Economic thresholds...

We propose a new point of view in the long-standing problem where several voters have expressed a linear order relation (or ranking) over a set of candidates. For a ranking a > b > c to represent a group’s opinion, it would be logical that the strength with which a > c is supported should not be less...

The article deals with notions of fuzzy equivalences, where transitivity is defined by the use of a fuzzy conjunction. In particular fuzzy C-equivalences and fuzzy α-C-equivalences are considered. Moreover, the problem of the preservation of their axioms by some aggregation functions is examined....

In many models for real-world problems such as the law of conservation of energy, the sum of parameters must be zero. In this paper, we investigate the problem of adding fuzzy numbers using the extension principle based on the concept of the joint possibility distribution. In particular, we present a...

The objective of this work is to associate the concepts of fuzzy rough sets and fuzzy topologies with fuzzy transform. It is shown here that the fuzzy transform can be viewed as fuzzy approximation operators studied in the operator-oriented view of fuzzy rough set theory and the use of fuzzy rough set...

In this paper the results of rule-base construction parameter optimization for a multi-stroke fuzzy character recognizer are compared. The experiment covers the investigation of the optimal number of samples used to build the rule-base and the parameter of the method to generate fuzzy sets from the training...

We present methods to find (significant) frequent synchronous patterns in event sequences, using a graded notion of synchrony that captures both the number of instances of a pattern as well as the precision of synchrony of its constituting events. Since transferring earlier work (using a binary notion...

The linguistic description of data intends to provide texts that convey the most important information contained in the data. One of the main tasks to be carried out in order to build a linguistic description is the extraction and representation of the knowledge to be transmitted. To perform this task,...

Our paper deals with constructions of upper and lower general aggregation operators, which are based in their definitions on a fuzzy equivalence relation. We study some properties of these aggregation operators which are important in the context of aggregation of fuzzy sets. In particular we consider...

In recent years, Fuzzy Time Series have been considered a promising tool to deal with forecasting problems due to the ease to model the problems, the satisfactory results obtained and also to the low computational cost required. However, the long experience with traditional methods coming from statistics,...

The present research is a consequent step in an ongoing research of a novel approach for decision support, called InterCriteria Analysis, which aims at identification of specific correlations between criteria in a decision making processes, using the concepts of intuitionistic fuzziness and index matrices....

In this paper we present a new class of fuzzy sets, paired fuzzy sets, that tries to overcome any conflict between families of fuzzy sets that share a main characteristic: that they are generated from two basic opposite fuzzy sets. Hence, the first issue is to formalize the notion of opposition, that...

We give a normalized expression for the solutions to the initial value problem for some linear fuzzyinterval differential equations by using a general notation which allows the combination of two types of differences. By switching between these types of differences, we derive several expressions for...

In this paper, we introduce Interpolative Boolean alge-bra (IBA) as a suitable algebra for intuitionistic fuzzy sets (IFSs). IBA is [0,1]-valued realization of Boolean algebra, consistent with Boolean axioms and theorems. IFS theory takes into account both membership and non-membership function, so it...

Today, a large amount of uncertain data is produced by several applications where the management systems of traditional databases incuding indexing methods are not suitable to handle such type of data. In this paper, we propose an inverted based index method for effciently searching uncertain categorical...

In this paper we introduce a new notion of generalized metric, called i-metric. This generalization is made by changing the valuation space of the distance function. The result is an interesting distance function for the set of fuzzy numbers of Interval Type with non negative fuzzy numbers as values....

In the present paper, we connect some old reflections about the relationships existing between the theory of fuzzy sets and cybernetics with modern, contemporary analyses of the crucial (better: unavoidable) role that fuzziness plays in the attempts at scientifically describing aspects of information...

In the present paper, we connect some old reflections about the relationships existing between the theory of fuzzy sets and cybernetics with modern, contemporary analyses of the crucial (better: unavoidable) role that fuzziness plays in the attempts at scientifically describing aspects of information...